How future of IIOT allows the factory of the future


Trillion-Dollar projections on the expansion size of the market are urging companies to capitalize on the Industrial IoT (IIOT). However, for many, it is still not clear how industries should be applied to start making a hyperocerve and agile reality of the future of IIOT.

As the fourth industrial revolution transforms manufacturing and management of materials, companies continue to seek ways to create value of convergent technologies. But, what are the steps that companies should take to collect an effective agenda of action? It seems essential that the industrial Internet implementation is incorporated into the strategy and business development of the company. In other words, the executive bosses must adopt the change. To advance decision making at the right level, CEOs should be included from the beginning, possibly as the main sponsor of the initiative. Only IT officials cannot conduct a real real transformation.

To start the transformation manufacturers, they must define a specific set of objectives, which will be evaluated and validated initially in a pilot project, before the implementation at scale of an end-to-end industrial IOT solution. The next step is to implement an industrial Internet pilot in an installation, or in a specific production line, which will be used as a case study to learn how IOT works in this particular industrial environment. The pilot installation is returned to work and develops according to the observations. After the test phase, it is easy for a company to apply the same principles, with adequate adjustments, at scale to other facilities.

It is easier to justify large investments in industrial Internet in environments where industrial Internet is incorporated into production to the transition directly to automated and advanced IITR environments. The transition phase is not very much complicated if the existing infrastructure is simple and easy to understand, because there are fewer things that should be counted or should check before applying the new solutions.

A case in point is Romania, where the Internet infrastructure is already upstairs in Europe. The Romanian infrastructure was created quite recently compared to the richest European countries, and therefore, the entire web is more modern than Finland, for example.

Future of IIOT

Industrial Internet in practice

Industrial IoT applications are already a reality. There are dozens of use cases different from III in companies. Companies are developing IOT applications that work, and have begun to make a difference. For example, transport and storage benefit from automated vehicles and asset follow-up. In manufacturing, predictive maintenance (PDM) and asset performance management (APM]) are key areas where industrial Internet increases value creation.

Source: Momenta Partners White Book: Carrying out the opportunity in predictive maintenance analysis – August 17, 2017

Predictive maintenance maintains assets and working, decreasing operating costs and millions of dollars savings. The transmission of data from sensors and devices can be used to quickly evaluate current conditions, recognize warning signals, deliver alerts and automatically activate the appropriate maintenance processes. The IIO coupled with AI or ML, therefore, converts maintenance into a dynamic, fast and automated task.

Other potential advantages include the increased life of the equipment, the greater security of the plant and less accidents with a negative impact on the environment.

The importance of edge analyzes.

Companies have been proactive to move the processing of future of IIOT to cloud services. However, it is not good or wise move to have everything in the cloud storage. During the critical stages of the manufacturing process, it is crucial that decisions can be made instantaneously. Here, manufacturers can benefit from Analytics Edge.

EDGE computing allows real-time analysis. Edge Analytics is a collection focus and data analysis where an automated analytical calculation is performed in the data in a sensor, network switch or other device instead of waiting for the data to be sent to a centralized data warehouse . IIOT can be complemented with open source hardware and software-based software based on Arduino, which allow some of the processes to be carried out on the site, on the edge of the network and close to the source of the data. EDGE computing helps ensure that the correct processing takes place at the right time, in the right place.

EDGE computing is a preferable option for the cloud in terms of security, since the patented data is kept within the company’s firewall. In addition, EDGE computing becomes vital when you need a real-time analysis and automated action to save critical mission production lines or installations of possible heavy damage.

Creating value with IIOT

There is no value in data without advanced machine learning algorithms. The value can be created so surprisingly simple when putting the data to work. The Peloton Tech truck peloton system is a case study that illustrates how IITR is already creating value. The future of IIOT system uses vehicle communication to vehicle to connect braking and acceleration between two trucks. The main system of truck controls the simultaneous acceleration and braking system of the entire fleet, and it also react faster than a human sensory system. What follows is a reduction in aerodynamic drag, which leads to companies that save around seven percent at the cost of fuel. In the terms of annual savings and benefits, this is a recorded breaking number.

In Europe, the truck companies, such as Scania and Volvo, have adopted the thought of the fleet of IIII. Courage is still needed to adopt innovations like these. Companies must begin to see emerging technology such as Industrial IoT, not as a threat which affects their business policy, but as the only way to survive in a matter of a few years because it is the future of every industry. That’s two or three years if you are an optimist, from five to ten if you are more conservative.

The simple capacity of the devices to take advantage of the data is not what the industrial Internet of things is about. Even if you have all the infrastructure and technology to obtain the data: the sensors, wifi, the gateway, the cloud and the ability to analyze the data, there is no value in it without AI, more specifically advanced automatic learning algorithms.

IOII is about AI or ML that analyze the data in real time to make decisions and act, most of the time several days or even weeks before a possible problem. This process results in real commercial results. Prescriptive analytics react autonomously, in real time: in a critical mission situation, a prescriptive system will decide autonomously what to do. This is where the edge analysis is imperative.

My point is: Independent industrial Internet cannot be considered. The real value comes from the way in which companies use IIT solutions enabled for AI and ML to analyze and process data.

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